Systems containing multiple microphones can detect directional sound by using beam forming techniques where the signals from at least two microphones are compared to observe phase shifts and magnitude differences. Processing signals from two different microphones capturing the same sounds requires equalization because the physical characteristics and magnitude responses may vary between microphones. These variations can exist even between microphones of the same make and model due to minor manufacturing variations. Variations can also be caused by many other factors, such as microphone boots, tube length differences, and other variations. Variations between microphones complicate processing signals from multiple microphone systems because applications, such as beam forming, assume that the differences in the signals measured at each microphone are attributable only to environmental and spacial differences, not differences in how the signals were measured. Accordingly, signal processing in multiple-microphone systems attempts to equalize the raw signals to improve the accuracy of signal processing calculations.
One conventional technique for equalizing is off-line calibration during system production. This technique requires manufacturing microphones with extremely low tolerance errors which increases the cost and sensitivity of the microphones. Another conventional technique for equalizing is self-calibration. On-line self-calibration using gain or magnitude response techniques include calculating propagation loss and phase matching. On-line self-calibration using frequency response techniques requires knowing the location of the control stimulus.
On-line self-calibration using magnitude response techniques generally operate by transforming the time domain signals for each microphone (e.g., two signals from two separate microphones) into the frequency domain and then calculating an equalization ratio based on the first and second signals across the frequency range. The equalization ratio is then applied to the frequency domain of the second signal in an attempt to match it to the first microphone. The adjusted second signal is then transformed back into the time domain, and further processing, such as beam forming calculations, may be performed with the first and second signals. This technique reduces the error introduced by variations in the two microphones, but introduces additional error in the equalization computations.
Manipulating the frequency domain of the second signal using the calculated equalization ratio across all frequencies and then converting back to the time domain introduces error in calculations. The magnitude response of the microphones varies across frequencies such that the calculated equalization ratio only approximates the magnitude differences of the two signals and does not account for varied magnitude responses of the different microphones at different frequencies. Furthermore, the signal generated by the Inverse Fast Fourier Transform (I-FFT) when converting the adjusted second signal from the frequency domain back to the time domain inherently introduces error because of the mathematical limitations of I-FFTs. Such a conventional technique is illustrated in FIG. 1, in which the frequency domain signal for x2[n] is taken from node 101, after conversion to frequency domain at block 105, and equalized at amplifier 102 using the ratio of the frequency domain responses calculated at processing block 103. The equalized frequency response of x2[n] is then transformed in I-FFT block 104.
Shortcomings mentioned here are only representative and are included simply to highlight that a need exists for improved electrical components, particularly for multiple microphone systems employed in consumer-level devices, such as mobile phones. Embodiments described herein address certain shortcomings but not necessarily each and every one described here or known in the art.